The evolving global energy environment is more closely connecting the needs of large industrial, commercial and institutional energy consumers with those of the power utilities and energy services companies. In some regions, deregulation of the electricity industry is introducing consumer choice, competition amongst energy suppliers, and significant demands on the electrical industry. Beyond price, large energy consumers are increasingly demanding higher value for their energy investment. Many businesses are likewise increasing their expectation that energy will be delivered at high levels of quality and reliability. These factors are driving both the suppliers and consumers of energy to seek better strategies to manage the cost and quality of the energy product and energy assets that produce, deliver, control and consume it. There are several fundamental challenges: the need to support the economic and efficient delivery, purchasing and use of energy; the need to guarantee higher levels of power quality and reliability; and, the need to supply the increasing demand for energy in a market based pricing system.
Users and suppliers of energy are well positioned to take advantage of these opportunities but the tools to effectively and efficiently manage energy resources and make informed decisions are lacking. There is a lack of understanding on what drives the costs and how they can be reduced by changes in the operational usage patterns of their particular business. Facility managers will also want to normalize usage patterns with respect to occupancy, temperature, weather and other variables in order to accurately project energy requirements into the future and also determine where further efficiencies can be realized.
Historically, energy management has been a difficult task to accomplish for a variety of reasons. Not all forms of energy can be stored successfully for long periods or, in some cases, at all. Purchasing energy to cover short falls can be expensive, so being able to predict and control the use of energy is an excellent way to reduce these costs. Before energy use can be predicted or controlled it must be measured, not only in real-time but also over a period of time to gather data on trends and cycles of energy usage. With historical energy usage data, predictions can be made how energy will be used in the future. Additionally, changes to energy usage can be patterned, modeled and analyzed using historical databases and other non-measured information to see how costs may change.
Using this information, changes in usage patterns can be implemented to optimize the usage of energy assets to meet the goals of the user. Likewise, over time the same energy measurement system can verify that the goals were actually realized, and if not, then help plan further changes as needed. This will help personnel to better manage capital expenditures, extend equipment life and economically schedule maintenance. Reliability of the network can be analyzed and weak points identified for further action. The costs of the loads can be apportioned to the actual uses of energy so the true costs of products and services can be realized.